1. The Field of the Invention
The present invention relates generally to real-time management of large-scale synthetic environment simulation. More specifically, the present invention provides real-time viewing, control and interaction of automatically generated, large, terrain and feature models consisting of heterogeneous data sets with multiple levels of detail, while providing correlated multi-sensor viewing and interaction of objects.
2. The State of the Art
To understand the benefits of the present invention, it is useful to briefly analyze a few of the many problems when implementing a large-scale synthetic environment simulation. It is useful when discussing this topic to use the real world application of battlefield simulations because of the substantial benefits which can be reaped from simulation of such environments.
A real-time simulation system must support deterministic, real-time handling of messages and events from both internal and external threads and processes. Because many simulated training tasks often involve controlling and interacting with dynamic entities, the system must support arbitrary real-time behaviors and interactions. A simulation system must support large, correlated, multi-sensor databases in order to supply a rich enough synthetic environment for effective training. It is important to understand that "large" means arbitrary in size, without the restriction of a "small" database which must fit within the system's virtual memory space or within its physical memory. State of the art databases can often exceed 50 Gigabytes of data.
One of the numerous problems in creating a real-time synthetic environment as described above is finding the right entity abstractions or models. If a model is too complex, it generally becomes inefficient and difficult to use. If too simple, its reuse and extension are restricted. Once the correct model is identified, it is then necessary to construct a database that will support multiple entity models and their relations. Ideally, the database provides multiple model transformations, multiple correlated views and incremental updating.
It is also essential that modeled entities behave correctly. Dynamic models, such as terrain and atmospheric effects, must act and interact in all important aspects as would the real-world entities if valid training is to occur.
What is lacking in the state of the art is a system which combines many disparate features which are typically spread throughout various applications for creating a large database. Furthermore, this combination of features should provide the ability to create the large database for a real-time synthetic environment which supports multiple models, wherein the models can all be based on a given set of source data, whether that data source defines terrain and/or a feature. A feature model should contain sufficient information such that one feature model can interact with another feature model without intervention. Likewise, a terrain model should provide the same information to enable automatic terrain-terrain interaction between terrain models without intervention by a user. Once modeled, the feature models and terrain models should be able to be localized to small regions of interest. The localized feature and terrain data should then be capable of being merged together where the features are reconciled with the local terrain upon which they rest to create at least a partially reconciled database. Furthermore, the database should provide the ability to be incrementally updated by modifying a single feature or terrain model without having to recompile the entire database.